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Association Asosiasi A Priori SIB6

Menerapkan Metode Asosiasi dengan Kasus Market Basket Analysis (MBA) menggunakan Algoritma Apriori untuk mengidentifikasi pola pembelian pelanggan berdasarkan jenis produk yang dibeli secara bersamaan. Hasil identifikasi tersebut kemudian dianalisis untuk membentuk paket promo sehingga meningkatkan target penjualan.

Applying the Association Method with the Market Basket Analysis (MBA) Case using the Apriori Algorithm to identify customer purchasing patterns based on the types of products purchased simultaneously. The identification results are then analyzed to form a promo package so as to increase sales targets.
This workflow is a fulfillment of the NF Academy Codeless Data Science SIB-6 Final Project assignment.

Dataset : Bakery.csv
Link : https://www.kaggle.com/datasets/akashdeepkuila/bakery

grup 1 kelompok 1
Ketua : Deddy Irawan
Anggota : Abdulla Azzam Robbani, Dwi Annisa Maharani, Jannatul Aulia, Novita Syahputri

URL: Bakery Dataset https://www.kaggle.com/datasets/akashdeepkuila/bakery

Preparation & EDA Add model & remove duplicate Evaluation & Get Result set MinimumSupport association rules("A priori" algorithm)Node 204add items nameNode 220Statistic DoubleConfiguration Association RuleLearner (Borgelt) CSV Reader DuplicateRow Filter Perbandinganper Day Visualisasi Table Writer Extract Result Statistics View Preparation Preparation & EDA Add model & remove duplicate Evaluation & Get Result set MinimumSupport association rules("A priori" algorithm)Node 204add items nameNode 220StatisticDoubleConfiguration Association RuleLearner (Borgelt) CSV Reader DuplicateRow Filter Perbandinganper Day Visualisasi Table Writer Extract Result Statistics View Preparation

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